Exploring the diversity in the impact of colors of rating scales on user's rating behavior

User-generated ratings have become an integral part of data-driven systems, yet they are known to be susceptible to rating bias that can distort the true ratings of users and can subsequently contaminate the effectiveness of the system. Earlier studies have discovered that different characteristics of a rating scale such as granularity, color, neutral point, etc. play a significant role in instigating bias in users' rating behavior. Amongst all, the research works done so far to explore the impact of colors used in rating scales have uncovered significant contradictory patterns of bias in user ratings. This research argues that because of their individuality, users' responses to the influence exerted by the color of the scale are diverse. Personality and culture are known as two consistent representatives of a person's individuality. Yet no attempt has been made to explore the diversity in individuals' responses to the influence of color of rating scales from the perspective of their personality and culture. In addition to it, while investigating the impact of color, the existing research works employed rating scales varying in multiple characteristics other than colors and consequently failed to capture the sole impact of color on users' rating behavior. This research addresses the problem by providing new empirical information about the impact of color-coded rating scales on users' rating behavior. A within-subject study was conducted to collect participants' responses on a demographic and a personality assessment questionnaire and their ratings on different products. The result shows that, extroverts tend to provide biased ratings in star-based scales with contrasting color combinations. On the other hand, collectivists exhibit a tendency to provide biased ratings under the influence of star-based and emoji-based scales with contrasting color combinations. The analysis also revealed some significant directions on how extroverts and collectivists adjust their ratings due to bias. Precisely, taking a personality and culture based approach can help to gain a thorough understanding of the impact of color-coded rating scales on users' rating behavior